Robust Face Recognition under Varying Light Based on 3D Recovery

This paper addresses face recognition under varying light via 3D reconstruction based on the techniques of shape from shading (SFS). First, we improve the geometric-based SFS by introducing the integrability constraint as one of the regular terms. This operation preserves the local curvedness of the recovered surface. Second, we propose a novel method to investigate human face recognition in the illumination varying case using local topographic information, such as curvedness and shape index extracted from intensity images by SFS algorithms. The experimental results have shown that the curvedness and shape index are suitable for representing 3D local features, and also it is insensitive to light variations since only 3D information is involved. Compared with typical face recognition approaches based on principal component analysis (PCA) plus linear discriminant analysis (LDA), the proposed method has demonstrated a better performance. This implies local topological properties are effective attributes for face recognition under light variations

[1]  Mubarak Shah,et al.  Shape from shading using linear approximation , 1994, Image Vis. Comput..

[2]  Rama Chellappa,et al.  SFS based view synthesis for robust face recognition , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).

[3]  Azriel Rosenfeld,et al.  Improved Methods of Estimating Shape from Shading Using the Light Source Coordinate System , 1985, Artif. Intell..

[4]  M. Turk,et al.  Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.

[5]  E. Rouy,et al.  A viscosity solutions approach to shape-from-shading , 1992 .

[6]  Edwin R. Hancock,et al.  Object Recognition Using Shape-from-Shading , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Rama Chellappa,et al.  Illumination-insensitive face recognition using symmetric shape-from-shading , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[8]  Zhaohui Wu,et al.  3D Face Recognition using Mapped Depth Images , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops.

[9]  David J. Kriegman,et al.  Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection , 1996, ECCV.

[10]  Amnon Shashua,et al.  The Quotient Image: Class-Based Re-Rendering and Recognition with Varying Illuminations , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Edwin R. Hancock,et al.  New Constraints on Data-Closeness and Needle Map Consistency for Shape-from-Shading , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  Alex Pentland,et al.  A simple algorithm for shape from shading , 1992, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[13]  Alex Pentland,et al.  Bayesian face recognition , 2000, Pattern Recognit..

[14]  David J. Kriegman,et al.  From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  David J. Kriegman,et al.  Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection , 1996, ECCV.

[16]  Azriel Rosenfeld,et al.  Face recognition: A literature survey , 2003, CSUR.

[17]  Michael J. Brooks,et al.  Shape and Source from Shading , 1985, IJCAI.

[18]  anonymous,et al.  Evaluation Report , 1990, The Aboriginal Child at School.

[19]  Berthold K. P. Horn SHAPE FROM SHADING: A METHOD FOR OBTAINING THE SHAPE OF A SMOOTH OPAQUE OBJECT FROM ONE VIEW , 1970 .

[20]  B. Sankur,et al.  3D Face Recognition , 2006, 2006 IEEE 14th Signal Processing and Communications Applications.

[21]  Rama Chellappa,et al.  Estimation of illuminant direction, albedo, and shape from shading , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[22]  Rama Chellappa,et al.  A Method for Enforcing Integrability in Shape from Shading Algorithms , 1988, IEEE Trans. Pattern Anal. Mach. Intell..

[23]  Olivier Faugeras,et al.  A mathematical and algorithmic study of the Lambertian SFS problem for orthographic and pinhole cameras , 2003 .

[24]  Ping-Sing Tsai,et al.  Shape from Shading: A Survey , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[25]  Hyeonjoon Moon,et al.  The FERET Evaluation Methodology for Face-Recognition Algorithms , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[26]  Zhaohui Wu,et al.  3D face recognition using local shape map , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

[27]  Katsushi Ikeuchi,et al.  Numerical Shape from Shading and Occluding Boundaries , 1981, Artif. Intell..